密谋：对多类别条形图进行排序

Question

排序多类别图表时遇到一些问题。

一些示例代码。

import pandas as pd
import plotly.graph_objects as go

data = [
    [0, "Born", 4, "Rhino"],  # commenting this line will also reverse sub category sorting
    [0, "Died", -1, "Rhino"],
    [1, "Born", 4, "Lion"],
    [1, "Died", -1, "Lion"],
    [2, "Born", 12, "Rhino"],
    [2, "Died", -5, "Lion"],
]
z_data = list(zip(*data))

df = pd.DataFrame({
    "tick": z_data[0],
    "category": z_data[1],
    "value": z_data[2],
    "type": z_data[3],
})
df = df.sort_values(by=['tick', 'category', 'value', 'type'])
print(df)
fig = go.Figure()
for t in df.type.unique():
    plot_df = df[df.type == t]
    fig.add_trace(go.Bar(
        x=[plot_df.tick, plot_df.category],
        y=abs(plot_df.value),
        name=t,
    ))
fig.update_layout({
    'barmode': 'stack',
    'xaxis': {
        'title_text': "Tick",
        'tickangle': -90,
    },
    'yaxis': {
        'title_text': "Value",
    },
})
fig.write_html(str("./diagram.html"))

您可以看到刻度2在刻度1之前。这是因为“犀牛”是第一个类型列表，将创建刻度0和2。 但是，现在如何正确地对条进行排序？

PS。 'barmode': 'stack'是有目的的。即使在本测试示例中未使用它。

Answer 1

我能够修正刻度线，但不能修正出生/死亡订单。我打算逐行绘制，所以我需要玩showlegend

数据

  def new
    @invoice = Invoice.new
  end

  def edit
  end

  def create
    @invoice = Invoice.new(invoice_params)

    respond_to do |format|
      if @invoice.save
        format.html { redirect_to project_financial_payment_milestone_invoices_path, notice: 'Invoice was successfully created.' }
        format.json { render :show, status: :created, location: @invoice }
      else
        format.html { redirect_to project_financial_payment_milestone_invoices_path}
        format.json { render json: @invoice.projecterrors, status: :unprocessable_entity }
      end
    end
  end

设置颜色

如果您有更多类型，这里有可以帮助您的答案。选中doc

import pandas as pd
import plotly.graph_objects as go
data = [
    [0, "Born", 4, "Rhino"],  # commenting this line will also reverse sub category sorting
    [0, "Died", -1, "Rhino"],
    [1, "Born", 4, "Lion"],
    [1, "Died", -1, "Lion"],
    [2, "Born", 12, "Rhino"],
    [2, "Died", -5, "Lion"],
]
# you don't really need to zip here
df = pd.DataFrame(data, columns=["tick", "category", "value", "type"])
df["value"] = df["value"].abs()

显示图例

我想在这里显示每种类型的首次出现的图例

color_diz = {"Rhino": "blue", "Lion": "red"}
df["color"] = df["type"].map(color_diz)

要绘制的数据

grp = df.groupby("type")\
        .apply(lambda x: x.index.min())\
        .reset_index(name="idx")

df = pd.merge(df, grp, on=["type"], how="left")

df["showlegend"] = df.index == df["idx"]

print(df)

情节

   tick category  value   type color  idx  showlegend
0     0     Born      4  Rhino  blue    0        True
1     0     Died      1  Rhino  blue    0       False
2     1     Born      4   Lion   red    2        True
3     1     Died      1   Lion   red    2       False
4     2     Born     12  Rhino  blue    0       False
5     2     Died      5   Lion   red    2       False

编辑

如果您有更多fig = go.Figure() for i, row in df.iterrows(): fig.add_trace( go.Bar(x=[[row["tick"]], [row["category"]]], y=[row["value"]], name=row["type"], marker_color=row["color"], showlegend=row["showlegend"], legendgroup=row["type"] # Fix legend )) fig.update_layout({ 'barmode': 'stack', 'xaxis': { 'title_text': "Tick", 'tickangle': -90, }, 'yaxis': { 'title_text': "Value", }, }) fig.show() ，则可以使用以下技巧。

首先，我生成不同的类型

type

然后我从doc中选择一个颜色序列并将其放在字典中

import string
import numpy as np
import pandas as pd
import plotly.express as px

df = pd.DataFrame({"type":np.random.choice(list(string.ascii_lowercase), 100)})

然后我将唯一的color_dict = {k:v for k,v in enumerate(px.colors.qualitative.Plotly)} 放在数据框上

type

然后我根据它们的索引为其分配颜色

df_col = pd.DataFrame({"type": df["type"].unique()})

最后，我合并到原始df

df_col["color"] = (df_col.index%len(color_dict)).map(color_dict)